[1]} introduced a piecewise convolutional neural network (PCNN) to improve relation extraction. [2]} applied the max-pooling operation across the entire sentence to get the single important feature from the entire sentence for a particular convolutional filter. In PCNN, the max-pooling operation is not performed for the entire sentence. Instead, the sentence is divided into three segments: from the beginning to the argument appearing first in the sentence, from the argument appearing first in the sentence to the argument appearing second in the sentence, and from the argument appearing second in the sentence to the end of the sentence. Max-pooling is performed in each of these three segments and for each convolutional filter to obtain three feature values. A sentence-level feature vector is obtained by concatenating all such feature values and is given to a feed-forward neural network with a softmax activation layer to classify the relation.
